Tests for take method check against object dtype for boolean inputs.

Author: aijams

pandas/core/arrays/numpy_.py

@@ -368,16 +368,10 @@ def take(
             indices, allow_fill=allow_fill, fill_value=fill_value, axis=axis
         )
         # See GH#62448.
-        if self.dtype.numpy_dtype in [
-            np.uint8,
-            np.uint16,
-            np.uint32,
-            np.uint64,
-            np.int8,
-            np.int16,
-            np.int32,
-            np.int64,
-        ]:
+        # TODO: Not all Pandas extension dtypes have an underlying Numpy dtype.
+        # I will need to handle the case where self.dtype doesn't have this
+        # attribute.
+        if self.dtype.kind in "iub":
             return type(self)(result, copy=False)
 
         return result

pandas/tests/arrays/numpy_/test_numpy.py

@@ -325,31 +325,56 @@ def test_factorize_unsigned():
     tm.assert_extension_array_equal(res_unique, NumpyExtensionArray(exp_unique))
 
 
-# TODO: Add the smaller width dtypes to the parameter sets of these tests.
 @pytest.mark.parametrize(
     "dtype",
-    [np.uint8, np.uint16, np.uint32, np.uint64, np.int8, np.int16, np.int32, np.int64],
+    [
+        np.bool,
+        np.uint8,
+        np.uint16,
+        np.uint32,
+        np.uint64,
+        np.int8,
+        np.int16,
+        np.int32,
+        np.int64,
+    ],
 )
 def test_take_assigns_floating_point_dtype(dtype):
     # GH#62448.
-    array = NumpyExtensionArray(np.array([1, 2, 3], dtype=dtype))
+    if dtype == np.bool:
+        array = NumpyExtensionArray(np.array([False, True, False], dtype=dtype))
+        expected = np.dtype(object)
+    else:
+        array = NumpyExtensionArray(np.array([1, 2, 3], dtype=dtype))
+        expected = np.float64
 
     result = array.take([-1], allow_fill=True)
-
-    assert result.dtype.numpy_dtype == np.float64
+    assert result.dtype.numpy_dtype == expected
 
     result = array.take([-1], allow_fill=True, fill_value=5.0)
-
-    assert result.dtype.numpy_dtype == np.float64
+    assert result.dtype.numpy_dtype == expected
 
 
 @pytest.mark.parametrize(
     "dtype",
-    [np.uint8, np.uint16, np.uint32, np.uint64, np.int8, np.int16, np.int32, np.int64],
+    [
+        np.bool,
+        np.uint8,
+        np.uint16,
+        np.uint32,
+        np.uint64,
+        np.int8,
+        np.int16,
+        np.int32,
+        np.int64,
+    ],
 )
 def test_take_assigns_integer_dtype_when_fill_disallowed(dtype):
     # GH#62448.
-    array = NumpyExtensionArray(np.array([1, 2, 3], dtype=dtype))
+    if dtype == np.bool:
+        array = NumpyExtensionArray(np.array([False, True, False], dtype=dtype))
+    else:
+        array = NumpyExtensionArray(np.array([1, 2, 3], dtype=dtype))
 
     result = array.take([-1], allow_fill=False)